Attention Deficit Hyperactivity Disorder (ADHD) is a psychiatric disorder that has been characterized historically by the behavioral symptoms of inattention, impulsivity and hyperactivity. Estimates of the prevalence of this disorder range from five to fifteen percent of the school-aged population, making ADHD the most commonly diagnosed childhood psychiatric disorder [1]. The disorder occurs more commonly in males than in females, with ratios ranging from 4:1 to 9:1 [2]. Onset of the condition typically occurs prior to age seven.
Despite the prevalence of ADHD, there are no current laboratory measures considered useful in the diagnosis of ADHD [1, 2, 3]. Nevertheless, although there are no reliable tests to evaluate the assumed neurophysiological foundation of this disorder, stimulant medications like Ritalin, Adderall, Dexedrine and Cylert are routinely prescribed to millions of American children [1]. Adverse side effects including decreased appetite, insomnia, anxiety, irritability, and affective lability have been reported to occur in approximately 50% of the patients [4] with stomachaches and headaches reported in one third of the patients. In addition, estimates of the percentage of children responding to medication has been reported to be as low as 55-65% for children diagnosed with ADHD, Inattentive Type and 70-90% for ADHD, Combined Type [1]. A recently published review of studies of stimulant therapies [5] concluded that no positive clinical response was noted in 25 to 40% of the patients.
The frequency of adverse side effects and the limited efficacy of prescribed medications in approximately 50% of the children "diagnosed" with ADHD raises serious questions about the accuracy of current assessment procedures. The most common of the diagnostic procedures used in clinical practice include "interviews" and "behavioral rating scales." Such procedures are commonly utilized in evaluating psychiatric disorders since laboratory techniques are not available for the vast majority of conditions listed in the DIAGNOSTIC AND STATISTICAL MANUAL FOR MENTAL DISORDERS [2]. In assessing ADHD, behavioral rating scales such as the Child Behavioral Checklist [6], the Conners' Rating Scales [7], the ADHD Rating Scale [8] and the Attention Deficit Disorder Evaluation Scale [9] were developed to provide a database for comparing the behavioral observations of parents and teachers with "normative" populations. Similarly, continuous performance tests (CPTs), which measured capacity for vigilance and impulse control during visual and auditory tracking tasks [10, 11, 12], were developed to provide a more objective measure of the core symptoms of inattention and impulsivity.
While these measures were considered useful in the assessment process, particularly when combined with a thorough review of medical, developmental and family histories and an examination of intellectual functions and academic achievement, these tests could not be considered diagnostic for ADHD [1, 3]. Behavioral rating scales have limited diagnostic value due to a variety of rater biases [1, 13]. Similarly, the accuracy of CPTs is limited by the high rate of "false negative" scores [10, 11, 12, 14]. Consequently, in order to improve diagnostic accuracy, the development of additional assessment procedures appears necessary.
Overall, it appears that current procedures for medical examination are useful in differentiating ADHD from similar symptoms engendered by other physical disorders (e.g., thyroid disorders, anemia, hypoglycemia, allergies, diabetes). However, the absence of neurologically-based assessment procedures prevents physicians from examining the neurological causes of ADHD. Similarly, although conducting a thorough functional behavioral assessment at home and school can result in useful motivational strategies and instructional adaptations to promote the development and self-esteem of patients with a variety of behavioral disorders, such procedures do not target the neurological foundations of ADHD. This disconnection of treatment procedures from a coherent theoretical perspective regarding the etiology of ADHD is highly problematic, particularly when the most common form of treatment is the use of stimulant medications.
As with other medical conditions, a clear understanding of the causes of the illness or disorder is essential for the development of valid assessment procedures and effective, enduring treatments. During the past decade, multiple research teams, utilizing neuro-imaging techniques such as magnetic resonance imaging (MRI), positron emission tomography (PET) and single photon emission computed tomography (SPECT), have reported findings that support the hypothesis that anatomical and biochemical abnormalities of the pre-frontal cortex constitute the physical basis of ADHD [15, 16, 17, 18, 19, 20, 21].
More specifically, hypoperfusion and low metabolic activity in the pre-frontal and caudate nuclei regions and anatomical differences in the caudate nucleus, the cingulate gyrus and in the cerebellum have been observed in patients diagnosed with ADHD. Overall, these studies have provided initial evidence of the importance of the frontostriatal circuitry in understanding the neurological basis of ADHD.
As researchers proceeded to clarify the neuroanatomical structures implicated in ADHD, three research teams [22, 23, 24] sought to examine QEEG characteristics of patients diagnosed with ADHD. The rationale for application of the QEEG process is based on an understanding of the neuroanatomical basis of EEG patterns. As noted by Lubar [25], EEG activity arises from intracortical loops which are modulated by groups of cells in the thalamus. The "firing" of these cell groups (called "pacemakers") are responsible for the electrical "rhythms" or "wave forms" which are recorded by EEGs based on input from surface electrodes. Of particular interest to researchers examining patients diagnosed with ADHD are low frequency rhythms (4-8 Hz: "theta"), faster wave forms called "beta" (16-20 Hz) recorded in frontal and midline locations and SMR waves (12-16 Hz) recorded above the sensorimotor cortex. A series of studies by Sterman [26] clearly demonstrated the relationship between these specific electrical "wave forms" as recorded on the surface and the activity of the ventrobasal thalamus; and clarified that signals from the sensory pathways are conveyed to the cerebral cortex through relay nuclei in the thalamus. It is this region that has been identified as potentially critical in the manifestation of ADHD symptoms through neuro-imaging studies.
The common hypothesis shared by each of the research teams was that if cortical slowing was evident on PET and SPECT examinations, then such slowing would be evident during a QEEG assessment. The first two teams [22, 23] used a complex statistical analysis (discriminant function analysis) using recordings from multiple cortical locations and a variety of QEEG measures (e.g., electrophysiological power, absolute and relative power in the "theta" and "beta" frequencies, as well as measures of coherence and hemispheric symmetry). While both of these teams noted cortical slowing on QEEG examination and were able to identify patients with ADHD with a high degree of accuracy (85-95%), their procedure was criticized due to the complexity of the analysis and the significant probability that because of the multiplicity of QEEG measures analyzed, certain QEEG measures would show significant differentiation due to chance alone. In order to address these criticisms, a simplified QEEG process was developed by the present inventors.
This invention proceeds from the earlier work of one of the inventors [27] and an extensive series of studies conducted by the two inventors [42, 43]. The current process developed for assessing patients for ADHD is a simplified neurometric procedure. Like other researchers who have utilized a computerized power spectral analysis (PSA) to study patterns of cortical activation, this procedure involves the collection of multiple, short periods of digitized EEG which are subjected to a Fast Fourier Transformation (FFT) algorithm [28]. The FFT derived data are averaged over all trials for a given experimental condition. The overall electrophysiological power (pW) can then be determined for various frequency bands at the various active electrode sites. The current invention, however, simplifies the number of frequency bands and the number of active locations. It is based on an examination of the electrophysiological power produced within two frequency bands (4-8 Hz and 13-21 Hz) recorded at one active site (the vertex: Cz) with ear references.
Initially examined was the relationship between ADHD and a ratio of the electrophysiological output (pW) produced within the theta band (4-8 Hz) to that recorded at 13-21 Hz. This theta/beta power ratio was calculated from 19 locations as individuals completed the following tasks: eyes open baseline; eyes closed baseline; reading silently; completing visual-motor tasks; listening. Consistent with emerging neuroanatomical models of ADHD, it was hypothesized that evidence of excessive cortical slowing (i.e., a higher ratio of slow wave activity relative to "fast" EEG activity) would be noted in individuals diagnosed with ADHD. The results of this initial study supported the hypothesis. Significant group differences were noted in the theta/beta power ratios obtained at multiple cortical sites with Cz and Fz appearing the most promising for consideration in the development of an assessment procedure based on PSA.
Since the initial test of the validity of examining the theta/beta power ratio could be criticized for evaluating numerous cortical sites (i.e., at p&lt;0.05; 1 of 20 sites would be expected to yield significant differences due to chance alone), further development of a neurometric process for assessing ADHD required simplification of the scanning procedure. Since earlier research [29] had indicated that QEEG recordings at Cz best differentiated ADHD from non-ADHD controls, this location was selected for further testing. In subsequently reported research [24], the inventors conducted a spectral analysis of the electrophysiological output (theta/beta power ratio) at a single, midline location (Cz) in 482 individuals to test the hypothesis that electrophysiological indicators of slowing in the prefrontal cortex could serve as a basis for differentiating patients with ADHD from non-clinical control groups.
Participants were classified into three groups (ADHD, Inattentive; ADHD Combined; Control) based on the results of medical examination, a standardized clinical interview, behavioral rating scales and a CPT. QEEG recordings were obtained during an eyes fixed baseline, as well as reading, listening and drawing tasks. Theta/beta power ratios were obtained for each of the four conditions and the mean ratio was calculated for each individual. Using the mean and standard deviation of the control group to develop "critical values" for cortical slowing, participants were classified into ADHD or control groups on the basis of their average theta/beta ratio. Classification as ADHD or Control on the basis of QEEG findings alone was consistent with group placement based on interview and psychometric data in 88% of the cases. The sensitivity of the QEEG-derived "Attentional Index" was 86%; the specificity was 98%. Extensive examination of this process has been conducted [30] and is reported in "Test Results" hereinbelow.
Based on the results of previous QEEG studies using PSA, the present inventors developed and tested a simplified neurometric procedure for use in the assessment of ADHD. Due to the high cost and level of complexity of other types of neuro-imaging techniques, the development of a simplified scanning process is desirable to provide essential physiological data to physicians at a cost affordable to the general public. In addition, by reducing the complexity and cost of equipment needed for the scan, medical practitioners are now able to complete the evaluation in their private offices.